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International Journal of Production Research Volume 52, 2014 - Issue 22
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Articles

A fractal perspective-based methodological framework for supply chain modelling and distributed simulation with multi-agent system

Hua DaiSchool of Economics and Management, Tongji University, Shanghai, China;College of Computer Science, Hunan Institute of Science and Technology, Yueyang, China
,
Jie LinSchool of Economics and Management, Tongji University, Shanghai, ChinaCorrespondence[email protected]
&
Qingqi LongCollege of Information, Zhejiang University of Finance & Economics, Hangzhou, China
Pages 6819-6840 | Received 19 Oct 2012, Accepted 22 Apr 2014, Published online: 21 May 2014

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Jingsi Huang & Jie Song. (2018) Optimal inventory control with sequential online auction in agriculture supply chain: an agent-based simulation optimisation approach. International Journal of Production Research 56:6, pages 2322-2338.
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Nagesh Shukla & Senevi Kiridena. (2016) A fuzzy rough sets-based multi-agent analytics framework for dynamic supply chain configuration. International Journal of Production Research 54:23, pages 6984-6996.
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Navin K. Dev, Ravi Shankar, Angappa Gunasekaran & Lakshman S. Thakur. (2016) A hybrid adaptive decision system for supply chain reconfiguration. International Journal of Production Research 54:23, pages 7100-7114.
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Saba Vahid, Nadia Lehoux, Luis A. de Santa-Eulalia, Sophie D'Amours, Jean-Marc Frayret & Uday Venkatadri. (2016) Supply chain modelling frameworks for forest products industry: a systematic literature review. INFOR: Information Systems and Operational Research 54:1, pages 52-75.
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Articles from other publishers (9)

Yang Yang & Fuzhong Nian. (2023) Reconstructing a fractal supply chain network based on geographical characteristics. Nonlinear Dynamics.
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Ziang Liu & Tatsushi Nishi. (2023) Data-driven evolutionary computation for service constrained inventory optimization in multi-echelon supply chains. Complex & Intelligent Systems.
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Ayşegül Bozdoğan, Latife Görkemli Aykut & Neslihan Demirel. (2022) An agent-based modeling framework for the design of a dynamic closed-loop supply chain network. Complex & Intelligent Systems 9:1, pages 247-265.
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Nurcan Deniz. 2021. Chaos, Complexity and Leadership 2020. Chaos, Complexity and Leadership 2020 121 130 .
Barbara Chilmon & Nicoleta S. Tipi. (2020) Modelling and simulation considerations for an end-to-end supply chain system. Computers & Industrial Engineering 150, pages 106870.
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M. Estela Peralta & Víctor M. Soltero. (2020) Analysis of fractal manufacturing systems framework towards industry 4.0. Journal of Manufacturing Systems 57, pages 46-60.
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Alexandra Fiedler, Dirk Sackmann & Hans-Dietrich Haasis. 2019. Logistics Management. Logistics Management 62 74 .
Rameshwar Dubey. 2019. Handbook of Ripple Effects in the Supply Chain. Handbook of Ripple Effects in the Supply Chain 287 308 .
Roberto Dominguez, Salvatore Cannella & Jose M. Framinan. (2015) SCOPE: A Multi-Agent system tool for supply chain network analysis. SCOPE: A Multi-Agent system tool for supply chain network analysis.

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